Elasticsearch vs KDB.AI
Elasticsearch
elastic.co
KDB.AI
kdb.aiSide by side
| Figure | Elasticsearch | KDB.AI |
|---|---|---|
| Price from | $99/mo | Free |
| Free plan | — | Yes |
| Free trial | Yes | Yes |
| Open source | — | — |
| Web | Yes | Yes |
| Linux | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 8 | 2 |
| Spec score · Vector Databases | 8.5 (#4) | 7.9 (#11) |
| Spec score · Ai Databases | 8.4 (#7) | 7.9 (#18) |
| Deployment | It can run on premises, in the cloud, across clouds, or as a managed serverless service. | The maker documents both a managed cloud Starter Edition and a self-managed Server Standard Edition. |
| Founded | 2012 | 1993 |
| Headquarters | Amsterdam, Netherlands, and Mountain View, California, United States | Newry, Northern Ireland, UK |
| Integrations | Elastic describes 350+ integrations and supports ingestion through Elastic Agent, connectors, APIs, language clients, and Logstash. | The documentation lists LangChain, Vector IO, and LlamaIndex integrations. |
| Search | It supports full-text, semantic, and hybrid search with filters, ranking, and reranking. | It supports hybrid search combining dense and sparse vector search, metadata filtering, and temporal similarity search. |
| Support | Elastic Cloud Hosted and Serverless offer four support tiers depending on subscription tier. | The cloud FAQ directs users to the Slack community or [email protected] for assistance. |
Plans
Elasticsearch
- BasicPriced on request
- Standard$99 a month
- Gold$114 a month
- Platinum$131 a month
- Enterprise$184 a month
- Elastic Cloud HostedPrice not published
- Elastic Cloud ServerlessPrice not published
- Self-managed ElasticsearchPriced on request
KDB.AI
- KDB.AI Cloud Starter EditionFree
- KDB.AI Server Standard EditionPriced on request
In their own words
Elasticsearch
Elasticsearch has no write-up on Specifiction yet; its figures are above.
KDB.AI
KDB.AI is a vector database and search engine for building AI applications with real-time data. Its hybrid search combines dense and sparse vector search with metadata filtering and temporal similarity search. It supports retrieval-augmented generation using unstructured text, video, audio, and image data. Listed vector indexes include Flat, qFlat, IVF, IVFPQ, HNSW, qHNSW, and BM25. Documentation lists integrations with LangChain, Vector IO, and LlamaIndex, while native NVIDIA cuVS integration enables GPU-accelerated vector search. Deployment options include a managed Cloud Starter Edition and a self-managed Server Standard Edition. The free Cloud Starter Edition provides 4 GB of memory per instance, 30 GB of storage, and a 10 MB query size. Its agreement makes no commitment to availability or uptime and provides the service without warranty. The cloud FAQ points users to a Slack community or [email protected] for assistance. The maker presents research assistants, portfolio management, real-time alpha and beta extraction, and image processing as use cases. KDB.AI is offered through API, web, and self-hosted platforms.